{"id":"https://openalex.org/W4206222751","doi":"https://doi.org/10.1109/bigdata52589.2021.9671926","title":"Approximate High Dimensional Graph Mining With Matrix Polar Factorization: A Twitter Application","display_name":"Approximate High Dimensional Graph Mining With Matrix Polar Factorization: A Twitter Application","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4206222751","doi":"https://doi.org/10.1109/bigdata52589.2021.9671926"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671926","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044250636","display_name":"\u0393\u03b5\u03ce\u03c1\u03b3\u03b9\u03bf\u03c2 \u0394\u03c1\u03b1\u03ba\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2","orcid":"https://orcid.org/0000-0002-0975-1877"},"institutions":[{"id":"https://openalex.org/I187792471","display_name":"Ionian University","ror":"https://ror.org/01xm4n520","country_code":"GR","type":"education","lineage":["https://openalex.org/I187792471"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Georgios Drakopoulos","raw_affiliation_strings":["Ionian University"],"affiliations":[{"raw_affiliation_string":"Ionian University","institution_ids":["https://openalex.org/I187792471"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088268250","display_name":"Eleanna Kafeza","orcid":"https://orcid.org/0000-0001-9565-2375"},"institutions":[{"id":"https://openalex.org/I91044093","display_name":"Zayed University","ror":"https://ror.org/03snqfa66","country_code":"AE","type":"education","lineage":["https://openalex.org/I91044093"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Eleanna Kafeza","raw_affiliation_strings":["Zayed University"],"affiliations":[{"raw_affiliation_string":"Zayed University","institution_ids":["https://openalex.org/I91044093"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061448936","display_name":"Phivos Mylonas","orcid":"https://orcid.org/0000-0002-6916-3129"},"institutions":[{"id":"https://openalex.org/I187792471","display_name":"Ionian University","ror":"https://ror.org/01xm4n520","country_code":"GR","type":"education","lineage":["https://openalex.org/I187792471"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Phivos Mylonas","raw_affiliation_strings":["Ionian University"],"affiliations":[{"raw_affiliation_string":"Ionian University","institution_ids":["https://openalex.org/I187792471"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065914489","display_name":"Spyros Sioutas","orcid":"https://orcid.org/0000-0003-1825-5565"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Spyros Sioutas","raw_affiliation_strings":["University of Patras"],"affiliations":[{"raw_affiliation_string":"University of Patras","institution_ids":["https://openalex.org/I174878644"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5044250636"],"corresponding_institution_ids":["https://openalex.org/I187792471"],"apc_list":null,"apc_paid":null,"fwci":3.4188,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.9391771,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4441","last_page":"4449"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.7645559310913086},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6540461182594299},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.5365313291549683},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5324094891548157},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5194132328033447},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.4487789571285248},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.410527765750885},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.38857632875442505},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.29474377632141113}],"concepts":[{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.7645559310913086},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6540461182594299},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.5365313291549683},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5324094891548157},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5194132328033447},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.4487789571285248},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.410527765750885},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.38857632875442505},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29474377632141113},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671926","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1974421439","https://openalex.org/W1996736088","https://openalex.org/W2022846189","https://openalex.org/W2048696001","https://openalex.org/W2088307891","https://openalex.org/W2096423888","https://openalex.org/W2132883347","https://openalex.org/W2148632362","https://openalex.org/W2471100147","https://openalex.org/W2547436936","https://openalex.org/W2564533995","https://openalex.org/W2581362412","https://openalex.org/W2605179182","https://openalex.org/W2758813627","https://openalex.org/W2795481904","https://openalex.org/W2795527331","https://openalex.org/W2796431263","https://openalex.org/W2883604340","https://openalex.org/W2904608878","https://openalex.org/W2945118073","https://openalex.org/W2961495769","https://openalex.org/W2963982425","https://openalex.org/W2964423333","https://openalex.org/W2998122931","https://openalex.org/W3007598526","https://openalex.org/W3010338999","https://openalex.org/W3034197430","https://openalex.org/W3042517483","https://openalex.org/W3042668868","https://openalex.org/W3046435230","https://openalex.org/W3048919154","https://openalex.org/W3074682879","https://openalex.org/W3080512189","https://openalex.org/W3097176524","https://openalex.org/W3097626113","https://openalex.org/W3101558399","https://openalex.org/W3111343554","https://openalex.org/W3115361341","https://openalex.org/W3135187275","https://openalex.org/W3137564253","https://openalex.org/W3153581588","https://openalex.org/W3155138594","https://openalex.org/W3164130883","https://openalex.org/W3168833755","https://openalex.org/W3174842734","https://openalex.org/W3181491388","https://openalex.org/W6766417816","https://openalex.org/W6787744380"],"related_works":["https://openalex.org/W2127243424","https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W34555840"],"abstract_inverted_index":{"At":[0],"the":[1,4,55,58,64,67,77,97,122,175],"dawn":[2],"of":[3,23,57,66,100,157,174],"Internet":[5],"era":[6],"graph":[7,60,116,181],"analytics":[8],"play":[9],"an":[10,118,164,171,214],"important":[11],"role":[12],"in":[13,129,213],"high-":[14],"and":[15,34,39,102,138,163,199],"low-level":[16],"network":[17,29],"policymaking":[18],"across":[19],"a":[20,46,92,114,146,152,155,158],"wide":[21],"array":[22],"fields":[24],"so":[25],"diverse":[26],"as":[27,89,105,107,132,154],"transportation":[28],"design,":[30],"supply":[31],"chain":[32],"engineering":[33],"logistics,":[35],"social":[36],"media":[37],"analysis,":[38],"computer":[40],"communication":[41],"networks,":[42],"to":[43,54,63,195],"name":[44],"just":[45],"few.":[47],"This":[48],"can":[49,169],"be":[50,170],"attributed":[51],"not":[52],"only":[53],"size":[56],"original":[59,176],"but":[61],"also":[62],"nature":[65],"problem":[68,95],"parameters.":[69],"For":[70],"instance,":[71],"algorithmic":[72],"solutions":[73,85],"depend":[74],"heavily":[75],"on":[76,205],"approximation":[78,173,182],"criterion":[79],"selection.":[80],"Moreover,":[81],"iterative":[82],"or":[83],"heuristic":[84],"are":[86],"often":[87,127],"sought":[88,128],"it":[90],"is":[91,126,145],"high":[93,98],"dimensional":[94],"given":[96],"number":[99],"vertices":[101],"edges":[103],"involved":[104],"well":[106],"their":[108],"complex":[109],"interaction.":[110],"Replacing":[111],"under":[112],"constraints":[113],"directed":[115],"with":[117,186,190,193],"undirected":[119,172],"one":[120],"having":[121],"same":[123],"vertex":[124,140,201],"set":[125],"applications":[130],"such":[131],"data":[133],"visualization,":[134],"community":[135],"structure":[136],"discovery,":[137],"connection-based":[139],"centrality":[141,202],"metrics.":[142],"Polar":[143],"decomposition":[144],"key":[147],"matrix":[148,153,206],"factorization":[149],"which":[150],"represents":[151],"product":[156],"symmetric":[159],"positive":[160],"(semi)definite":[161],"factor":[162],"orthogonal":[165],"one.":[166],"The":[167,179,209],"former":[168],"adjacency":[177],"matrix.":[178],"proposed":[180],"has":[183],"been":[184],"tested":[185],"three":[187],"Twitter":[188],"graphs":[189],"encouraging":[191],"results":[192],"respect":[194],"density,":[196],"Fiedler":[197],"number,":[198],"certain":[200],"metrics":[203],"based":[204],"power":[207],"series.":[208],"dataset":[210],"was":[211],"hosted":[212],"online":[215],"MongoDB":[216],"instance.":[217]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4}],"updated_date":"2026-03-15T09:29:46.208133","created_date":"2025-10-10T00:00:00"}